# NIH Reporter Grants Scraper (`nexgendata/nih-reporter-grants-scraper`) Actor Scrape NIH Reporter — NIH/CDC/AHRQ federal research grants. Project number, title, abstract, PIs, organization, award amount USD, fiscal year, dates, funding mechanism (R01/U01), program official. Universities, biotech BD, grant consultants, science journalism. - **URL**: https://apify.com/nexgendata/nih-reporter-grants-scraper.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** Business, Education, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 nih grants This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 🔬 NIH Reporter Grants Scraper — Federal Research Funding Intel **Pull every NIH / CDC / AHRQ federal research grant — direct from the official Reporter API. No API key, no paywall, no front-end scraping.** The NIH operates the largest biomedical research funding database in the world: ~76K active projects, $40+ billion in annual awards across 27 institutes (NCI, NIAID, NHLBI, NIMH, etc.). This Actor wraps `api.reporter.nih.gov/v2/projects/search` and ships clean rows for university research-administration teams, biotech BD, grant-writing consultants, science journalism, and competitive-intel desks. ### What you get (per grant) - `project_num`, `core_project_num`, `appl_id` — unique IDs - `project_title`, `abstract` (full text), `phr_text` (public health relevance) - `principal_investigators[]` — first/last name, full name, contact-PI flag, profile_id - `contact_pi_name` — formatted "LASTNAME, FIRSTNAME" - `program_officers[]` — NIH staff overseeing the grant - `organization_name` + `_city` / `_state` / `_country` / `_zip` / `_uei` - `organization_type` — e.g. "Schools of Medicine", "Schools of Public Health" - `award_amount_usd`, `direct_cost_usd`, `indirect_cost_usd` - `fiscal_year`, `project_start_date`, `project_end_date`, `award_notice_date` - `funding_mechanism` — text label (e.g. "Research Project Grants") - `activity_code` — R01, U01, R21, P01, F31, K08, etc. - `agency_code`, `ic_abbreviation`, `ic_name` — which institute funded it - `study_section` — peer-review group that scored it - `opportunity_number` — the originating FOA / NOFO - `cong_dist` — congressional district (LA-02, CA-09, etc.) - `spending_categories`, `spending_categories_desc` — RCDC categorization - `is_active`, `is_new_award`, `covid_response`, `arra_funded` - `geo_lat` / `geo_lon`, `project_detail_url` ### Six high-leverage use cases 1. **Pharma BD: who's working on my mechanism?** — set `organizationName: "Mass General Brigham"` and pull every active oncology immunotherapy grant, then build outreach from named PIs. 2. **University competitive intel** — research-administration sets `agencies: ["NIH"]` and groups by `organizationName` to compare YoY award totals against peer institutions. 3. **Grant-writing consultant lead-gen** — given a list of newly-funded R21s (`activity_code: "R21"`), reach out to PIs about transition-to-R01 services. 4. **Science journalism** — set `piLastName: "Fauci"` (or any newsmaker scientist) and pull every grant they're on. 5. **Biotech investor screening** — filter to `minAwardAmount: 5000000` to surface mega-grants and the labs running them. 6. **Public-health policy research** — pull all CDC and AHRQ grants in `spending_categories_desc: "Health Disparities"` for econometric analysis. ### JSON quick start ```json { "fiscalYears": [2025], "agencies": ["NIH"], "organizationName": "Stanford", "maxProjects": 25 } ```` POST to `https://api.apify.com/v2/acts/nexgendata~nih-reporter-grants-scraper/runs?token=YOUR_TOKEN`. ### Python SDK example ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("nexgendata/nih-reporter-grants-scraper").call( run_input={ "fiscalYears": [2025], "agencies": ["NIH"], "organizationName": "Stanford", "maxProjects": 25, } ) total = sum(item["award_amount_usd"] or 0 for item in client.dataset(run["defaultDatasetId"]).iterate_items()) print(f"Stanford NIH FY2025 awards (sample): ${total:,.0f}") ``` ### cURL one-liner ```bash curl -X POST "https://api.apify.com/v2/acts/nexgendata~nih-reporter-grants-scraper/runs?token=$APIFY_TOKEN" \ -H "content-type: application/json" \ -d '{"fiscalYears":[2025],"agencies":["NIH"],"organizationName":"Stanford","maxProjects":25}' ``` ### Pipe the output anywhere - **Zapier** — daily watcher → new R01 awards in your therapeutic area → Slack - **Make.com** — Apify trigger → CRM enrichment with named PIs → Mailchimp - **n8n** — Apify run → Postgres warehouse → BI dashboard for VP Research - **Vector DB** — embed `abstract` text for semantic search across all NIH-funded science ### Pricing — pay only for what you get | Event | Cost | |---|---| | Actor start | $0.00005 (one-time per run, scaled by GB-RAM) | | Each grant | **$0.05** | Pull all FY2025 active R01s at one institution (~200 grants) for ~$10. The full annual NIH portfolio (~80K active projects) is ~$4,000. Compare to Dimensions ($25K+/yr), Lens.org ($10K+/yr), or Pivot-RP ($15K+/yr) — and you own the raw data forever. **Cost calculator:** `grants × $0.05 + $0.00005 × memoryGB`. No subscription, no minimum. ### FAQ **Q. Is this real-time?** A. The Reporter database refreshes weekly. Newly issued awards appear within 7–14 days of the award notice. **Q. Are subprojects included?** A. Yes — multi-component awards (P01, U54, etc.) include subproject rows where `subproject_id` is non-null in the source. The shaped record uses `appl_id` for uniqueness. **Q. What about non-NIH HHS grants (HRSA, FDA)?** A. NIH Reporter covers NIH + CDC + AHRQ + a few other HHS agencies. For broader federal grant coverage including HRSA, FDA, NSF use [USAspending Federal Awards Scraper](https://apify.com/nexgendata/usaspending-federal-awards-scraper). **Q. How accurate is the abstract field?** A. Abstracts come straight from the funded proposal's Section A. They're updated as the grant evolves through renewals. **Q. Can I get historical grants?** A. Yes. Reporter has data going back to FY1985. Pass any `fiscalYears` array, e.g. `[2015, 2016, 2017]`. **Q. Do you handle the JSON RPC quirks?** A. The Reporter API has nested `criteria` shape and uses POST not GET. We handle pagination, retries, and field shaping; you just supply human-friendly inputs. ### Related actors from the same author - **[USAspending Federal Awards Scraper](https://apify.com/nexgendata/usaspending-federal-awards-scraper)** — broader fed contracts/grants, $0.08/award. - **[SEC EDGAR Search](https://apify.com/nexgendata/sec-edgar-search)** — public-company filings (companion finance dataset). - **[Government Contracts Search](https://apify.com/nexgendata/government-contracts-search)** — SAM.gov contract opportunities. ### Try the full nexgendata fleet [Browse 170+ scrapers](https://apify.com/nexgendata?fpr=2ayu9b) — SEC EDGAR, government contracts, ATS jobs, FEC, court records, real estate, MCP servers and more. Get $5 free Apify credit when you sign up via that link. *** Built and maintained by the [nexgendata](https://apify.com/nexgendata) team. Bug reports & feature requests welcome via Apify Console messaging. # Actor input Schema ## `fiscalYears` (type: `array`): Federal fiscal years (e.g. \[2025] for FY2025). NIH FY runs Oct 1 → Sept 30. Multiple years OK. ## `agencies` (type: `array`): Funding agencies to include. Common values: NIH, CDC, AHRQ, NIDDK. NIH is the parent for the 27 ICs (NCI, NIAID, NIMH, NHLBI, etc). ## `organizationName` (type: `string`): Filter to grants awarded to a specific organization. Case-insensitive partial match against org\_name (e.g. 'Stanford'). ## `piLastName` (type: `string`): Filter to grants where a PI has this last name. Combine with piFirstName for tighter matches. ## `piFirstName` (type: `string`): Filter to grants where a PI has this first name. ## `minAwardAmount` (type: `integer`): Restrict to grants with award\_amount ≥ this value (USD). Useful for filtering out small admin supplements. ## `maxAwardAmount` (type: `integer`): Restrict to grants with award\_amount ≤ this value (USD). Useful for narrowing to small-grant programs. ## `maxProjects` (type: `integer`): Maximum number of grant projects to return (1–10000). Each project is one dataset row. ## Actor input object example ```json { "fiscalYears": [ 2025 ], "agencies": [ "NIH" ], "maxProjects": 5 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "fiscalYears": [ 2025 ], "agencies": [ "NIH" ], "organizationName": "", "piLastName": "", "piFirstName": "", "minAwardAmount": 0, "maxAwardAmount": 0, "maxProjects": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/nih-reporter-grants-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "fiscalYears": [2025], "agencies": ["NIH"], "organizationName": "", "piLastName": "", "piFirstName": "", "minAwardAmount": 0, "maxAwardAmount": 0, "maxProjects": 5, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/nih-reporter-grants-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "fiscalYears": [ 2025 ], "agencies": [ "NIH" ], "organizationName": "", "piLastName": "", "piFirstName": "", "minAwardAmount": 0, "maxAwardAmount": 0, "maxProjects": 5 }' | apify call nexgendata/nih-reporter-grants-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/nih-reporter-grants-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NIH Reporter Grants Scraper", "description": "Scrape NIH Reporter — NIH/CDC/AHRQ federal research grants. Project number, title, abstract, PIs, organization, award amount USD, fiscal year, dates, funding mechanism (R01/U01), program official. Universities, biotech BD, grant consultants, science journalism.", "version": "0.0", "x-build-id": "BjGeP3WEsveDvdLwO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~nih-reporter-grants-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-nih-reporter-grants-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~nih-reporter-grants-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-nih-reporter-grants-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~nih-reporter-grants-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-nih-reporter-grants-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "fiscalYears" ], "properties": { "fiscalYears": { "title": "Fiscal years", "type": "array", "description": "Federal fiscal years (e.g. [2025] for FY2025). NIH FY runs Oct 1 → Sept 30. Multiple years OK.", "items": { "type": "integer" } }, "agencies": { "title": "Agencies", "type": "array", "description": "Funding agencies to include. Common values: NIH, CDC, AHRQ, NIDDK. NIH is the parent for the 27 ICs (NCI, NIAID, NIMH, NHLBI, etc).", "items": { "type": "string" } }, "organizationName": { "title": "Organization name (optional)", "type": "string", "description": "Filter to grants awarded to a specific organization. Case-insensitive partial match against org_name (e.g. 'Stanford')." }, "piLastName": { "title": "Principal Investigator last name (optional)", "type": "string", "description": "Filter to grants where a PI has this last name. Combine with piFirstName for tighter matches." }, "piFirstName": { "title": "Principal Investigator first name (optional)", "type": "string", "description": "Filter to grants where a PI has this first name." }, "minAwardAmount": { "title": "Min award amount USD (optional)", "minimum": 0, "type": "integer", "description": "Restrict to grants with award_amount ≥ this value (USD). Useful for filtering out small admin supplements." }, "maxAwardAmount": { "title": "Max award amount USD (optional)", "minimum": 0, "type": "integer", "description": "Restrict to grants with award_amount ≤ this value (USD). Useful for narrowing to small-grant programs." }, "maxProjects": { "title": "Max projects", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of grant projects to return (1–10000). Each project is one dataset row.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```